There are a wide array of technologies directed to in vivo imaging of mammals—for example, bioluminescence, fluorescence, tomography, and multimodal imaging technologies. In vivo imaging of small mammals is performed by a large community of investigators in various fields, e.g., oncology, infectious disease, and drug discovery.
In vivo imaging often involves the use of reagents, such as fluorescent probes, for non-invasive spatiotemporal visualization of biological phenomena inside a live animal. For example, fluorescence molecular tomography (FMT) involves in vivo imaging of mammals for quantitative analysis of administered and/or endogenous probes. In vivo microCT imaging, is an x-ray-based technology that can image tissues, organs, and non-organic structures with an extremely high resolution. MicroCT has evolved quickly, requiring low dose scanning and fast imaging protocols to facilitate multi-modal applications and enable longitudinal experimental models. Multi-modal imaging involves the fusion of images obtained in different ways, for example, by combining FMT, PET, MRI, CT, and/or SPECT imaging data.
Acquisition of such in vivo images can be time consuming, and rapid analysis of the acquired images is key to the efficiency of the process. Often, it is desirable to focus imaging efforts on only those portions of the mammal interior to the rib cage, which contains many organs of interest and for which advanced image analysis is needed. Advanced image analysis may involve, for example, advanced tomographic reconstruction for the quantitative analysis of an administered or endogenous probe in one or more target organs of the mammal. The portions of an image outside those target organs may not be important to the analysis, and processing time spent on those portions is wasted and results in reduced efficiency.
There is a need for a highly efficient method for detecting regions of interest of an in vivo mammalian image in order to eliminate unnecessary processing of unimportant regions of the image and reduce overall image processing time without losing important image detail.